%0 Conference Paper %1 ChangSu:2005 %A Su, Chang %A Gao, Yang %A Yang, Jianmei %A Luo, Bin %B Hybrid Intelligent Systems, 2005. HIS '05. Fifth International Conference on %D 2005 %K ai crawl ontology p:diss p:holmes socialnetwork %P 6 pp.- %R 10.1109/ICHIS.2005.19 %T An efficient adaptive focused crawler based on ontology learning %U http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1587729 %X The enormous growth of the World Wide Web has made it important to perform resource discovery efficiently. Consequently, several new ideas have been proposed; among them a key technique is focused crawling which is able to crawl particular topical portions of the World Wide Web quickly without having to explore all Web pages. In this paper, we present an intelligent focused crawler algorithm in which we embed ontology to evaluate the page's relevance to the topic. Compared with other algorithms using domain knowledge, our algorithm can evolve the ontology automatically during crawl process. Considering the instinct characteristics of the ontology, propagation has also been imported to accelerate the evolution of the ontology. We applied our approaches in several tasks and provided an empirical evaluation which has shown promising results. %@ 0-7695-2457-5

@inproceedings{ChangSu:2005, abstract = {The enormous growth of the World Wide Web has made it important to perform resource discovery efficiently. Consequently, several new ideas have been proposed; among them a key technique is focused crawling which is able to crawl particular topical portions of the World Wide Web quickly without having to explore all Web pages. In this paper, we present an intelligent focused crawler algorithm in which we embed ontology to evaluate the page's relevance to the topic. Compared with other algorithms using domain knowledge, our algorithm can evolve the ontology automatically during crawl process. Considering the instinct characteristics of the ontology, propagation has also been imported to accelerate the evolution of the ontology. We applied our approaches in several tasks and provided an empirical evaluation which has shown promising results.}, added-at = {2008-06-12T12:56:59.000+0200}, author = {Su, Chang and Gao, Yang and Yang, Jianmei and Luo, Bin}, biburl = {https://www.bibsonomy.org/bibtex/2f31af1846cee54cd3a42525e2441b92a/enterldestodes}, booktitle = {Hybrid Intelligent Systems, 2005. HIS '05. Fifth International Conference on}, description = {IEEEXplore# An efficient adaptive focused crawler based on ontology learning}, doi = {10.1109/ICHIS.2005.19}, interhash = {0641699a9acee3b1052d91f0120e7ccf}, intrahash = {f31af1846cee54cd3a42525e2441b92a}, isbn = {0-7695-2457-5}, keywords = {ai crawl ontology p:diss p:holmes socialnetwork}, pages = {6 pp.-}, timestamp = {2009-03-03T12:34:31.000+0100}, title = {An efficient adaptive focused crawler based on ontology learning}, url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1587729}, year = 2005 }